Paired T-Test Calculator

Perform paired t-test calculations online with detailed statistical results including t-statistic, p-value, and confidence intervals.

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About This Tool

This online paired t-test calculator allows researchers, students, and analysts to perform statistical hypothesis testing on paired samples. Enter your paired observations (such as before-and-after measurements), set your significance level, choose your alternative hypothesis, and get comprehensive results including the t-statistic, degrees of freedom, p-value, confidence interval, and test conclusion. The tool is perfect for medical studies, psychological experiments, quality control assessments, and any research involving matched pairs or repeated measurements on the same subjects.

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How to Use

Enter your paired data in the table (Group 1 and Group 2 columns)
Add more pairs if needed using the 'Add Pair' button
Set your significance level (alpha) - default is
Choose your alternative hypothesis (two-tailed, greater than, or less than)
Click 'Calculate Paired T-Test' to perform the statistical analysis
View detailed results including t-statistic, p-value, confidence interval, and test conclusion
Use 'Clear All' to reset the calculator for a new analysis

Frequently Asked Questions

Find Quick Answers

What is a paired t-test?

A paired t-test (also called dependent samples t-test) is a statistical procedure used to determine whether the mean difference between two sets of paired observations is statistically significant. It's used when measurements are taken from the same subjects under two different conditions (e.g., before and after treatment).

When should I use a paired t-test?

Use a paired t-test when you have two measurements from the same subjects or matched pairs, such as pre-test and post-test scores, measurements before and after treatment, or matched case-control studies. The test assumes the differences between pairs are normally distributed.

What do the results mean?

The t-statistic measures the size of the difference relative to the variation in your sample data. The p-value indicates the probability of observing your results if there was no actual difference. If p-value < significance level (alpha), you reject the null hypothesis and conclude there is a statistically significant difference between the paired groups.

What is the difference between one-tailed and two-tailed tests?

A two-tailed test checks for any difference (greater or less than) between the paired groups. A one-tailed test checks specifically for a difference in one direction (either greater than or less than). Use one-tailed tests only when you have a specific directional hypothesis before collecting data.

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